Title: Efficient Bayesian Inference for Stochastic Volatility (SV)
Models
Description: Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models with and without asymmetry (leverage) via Markov chain Monte Carlo (MCMC) methods. Methodological details are given in Kastner and Frühwirth-Schnatter (2014) <doi:10.1016/j.csda.2013.01.002> and Hosszejni and Kastner (2019) <doi:10.1007/978-3-030-30611-3_8>; the most common use cases are described in Kastner (2016) <doi:10.18637/jss.v069.i05> and the package vignette.
Author: Darjus Hosszejni [aut, cre] (<https://orcid.org/0000-0002-3803-691X>),
Gregor Kastner [aut] (<https://orcid.org/0000-0002-8237-8271>)
Maintainer: Darjus Hosszejni <darjus.hosszejni@wu.ac.at>
Diff between stochvol versions 3.0.3 dated 2020-11-24 and 3.0.4 dated 2021-02-09
stochvol-3.0.3/stochvol/inst/doc/article2.R |only stochvol-3.0.3/stochvol/inst/doc/article2.Rnw |only stochvol-3.0.3/stochvol/vignettes/article2.Rnw |only stochvol-3.0.4/stochvol/DESCRIPTION | 9 - stochvol-3.0.4/stochvol/MD5 | 51 ++++--- stochvol-3.0.4/stochvol/NEWS | 5 stochvol-3.0.4/stochvol/R/stochvol-package.R | 8 - stochvol-3.0.4/stochvol/R/wrappers.R | 2 stochvol-3.0.4/stochvol/build/partial.rdb |only stochvol-3.0.4/stochvol/build/vignette.rds |binary stochvol-3.0.4/stochvol/inst/CITATION | 129 ++++++++---------- stochvol-3.0.4/stochvol/inst/doc/article2.Rtex |only stochvol-3.0.4/stochvol/inst/doc/article2.pdf |binary stochvol-3.0.4/stochvol/inst/include/adaptation.hpp | 2 stochvol-3.0.4/stochvol/man/exrates.Rd | 2 stochvol-3.0.4/stochvol/man/stochvol-package.Rd | 6 stochvol-3.0.4/stochvol/man/svsample.Rd | 2 stochvol-3.0.4/stochvol/src/sampling_latent_states.cc | 4 stochvol-3.0.4/stochvol/src/sampling_main.cc | 8 - stochvol-3.0.4/stochvol/src/sampling_parameters.cc | 2 stochvol-3.0.4/stochvol/vignettes/Figures |only stochvol-3.0.4/stochvol/vignettes/article2.Rtex |only stochvol-3.0.4/stochvol/vignettes/ref.bib | 22 +-- 23 files changed, 132 insertions(+), 120 deletions(-)
Title: Regression Models with Break-Points / Change-Points Estimation
Description: Given a regression model, segmented `updates' it by adding one or more segmented (i.e., piece-wise linear) relationships. Several variables with multiple breakpoints are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>).
Author: Vito M. R. Muggeo [aut, cre]
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>
Diff between segmented versions 1.3-1 dated 2020-12-10 and 1.3-2 dated 2021-02-09
DESCRIPTION | 8 MD5 | 54 ++--- NAMESPACE | 74 +++---- NEWS | 9 R/aapc.r | 15 - R/broken.line.r | 19 + R/confint.segmented.R | 11 - R/intercept.r | 23 +- R/lines.segmented.R | 4 R/plot.segmented.R | 76 +++++-- R/points.segmented.r | 4 R/predict.segmented.r | 6 R/seg.Ar.fit.r | 2 R/seg.glm.fit.r | 2 R/seg.lm.fit.r | 2 R/slope.R | 12 - man/aapc.Rd | 5 man/broken.line.Rd | 5 man/confint.segmented.Rd | 5 man/intercept.Rd | 137 ++++++------- man/lines.segmented.Rd | 4 man/plot.segmented.Rd | 6 man/points.segmented.Rd | 4 man/predict.segmented.Rd | 3 man/seg.control.Rd | 2 man/segmented-package.Rd | 4 man/segmented.Rd | 482 +++++++++++++++++++++++------------------------ man/slope.Rd | 4 28 files changed, 535 insertions(+), 447 deletions(-)
Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra
Library
Description: 'Armadillo' is a templated C++ linear algebra library (by Conrad
Sanderson) that aims towards a good balance between speed and ease of
use. Integer, floating point and complex numbers are supported, as
well as a subset of trigonometric and statistics functions. Various
matrix decompositions are provided through optional integration with
LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the
header files from the templated 'Armadillo' library. Thus users do
not need to install 'Armadillo' itself in order to use
'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed
under Apache License 2; previous releases were under licensed as MPL
2.0 from version 3.800.0 onwards and LGPL-3 prior to that;
'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed
under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.
Armadillo requires a C++11 compiler.
Author: Dirk Eddelbuettel, Romain Francois, Doug Bates and Binxiang Ni
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Diff between RcppArmadillo versions 0.10.1.2.2 dated 2021-01-10 and 0.10.2.1.0 dated 2021-02-09
ChangeLog | 20 DESCRIPTION | 8 MD5 | 208 - build/partial.rdb |binary configure | 18 configure.ac | 2 inst/NEWS.Rd | 15 inst/doc/RcppArmadillo-intro.pdf |binary inst/doc/RcppArmadillo-sparseMatrix.pdf |binary inst/include/armadillo | 4 inst/include/armadillo_bits/BaseCube_bones.hpp | 3 inst/include/armadillo_bits/BaseCube_meat.hpp | 106 inst/include/armadillo_bits/Base_bones.hpp | 9 inst/include/armadillo_bits/Base_meat.hpp | 115 inst/include/armadillo_bits/Col_meat.hpp | 40 inst/include/armadillo_bits/Cube_bones.hpp | 6 inst/include/armadillo_bits/Cube_meat.hpp | 165 - inst/include/armadillo_bits/Mat_bones.hpp | 7 inst/include/armadillo_bits/Mat_meat.hpp | 256 -- inst/include/armadillo_bits/ProxyCube.hpp | 108 inst/include/armadillo_bits/Row_meat.hpp | 40 inst/include/armadillo_bits/SpBase_bones.hpp | 8 inst/include/armadillo_bits/SpBase_meat.hpp | 160 + inst/include/armadillo_bits/SpCol_meat.hpp | 10 inst/include/armadillo_bits/SpMat_bones.hpp | 13 inst/include/armadillo_bits/SpMat_meat.hpp | 281 -- inst/include/armadillo_bits/SpRow_meat.hpp | 6 inst/include/armadillo_bits/SpSubview_bones.hpp | 3 inst/include/armadillo_bits/SpSubview_meat.hpp | 58 inst/include/armadillo_bits/arma_cmath.hpp | 18 inst/include/armadillo_bits/arma_ostream_bones.hpp | 19 inst/include/armadillo_bits/arma_ostream_meat.hpp | 489 +++ inst/include/armadillo_bits/arma_rng.hpp | 23 inst/include/armadillo_bits/arma_version.hpp | 6 inst/include/armadillo_bits/arrayops_bones.hpp | 8 inst/include/armadillo_bits/arrayops_meat.hpp | 27 inst/include/armadillo_bits/auxlib_meat.hpp | 2 inst/include/armadillo_bits/config.hpp | 6 inst/include/armadillo_bits/constants.hpp | 35 inst/include/armadillo_bits/debug.hpp | 22 inst/include/armadillo_bits/def_blas.hpp | 87 inst/include/armadillo_bits/def_lapack.hpp | 728 ++--- inst/include/armadillo_bits/def_superlu.hpp | 16 inst/include/armadillo_bits/diagview_bones.hpp | 3 inst/include/armadillo_bits/diagview_meat.hpp | 48 inst/include/armadillo_bits/diskio_meat.hpp | 2 inst/include/armadillo_bits/eop_aux.hpp | 6 inst/include/armadillo_bits/eop_core_bones.hpp | 3 inst/include/armadillo_bits/eop_core_meat.hpp | 94 inst/include/armadillo_bits/field_meat.hpp | 124 inst/include/armadillo_bits/fn_cond.hpp | 13 inst/include/armadillo_bits/fn_eigs_gen.hpp | 263 +- inst/include/armadillo_bits/fn_eigs_sym.hpp | 132 - inst/include/armadillo_bits/fn_elem.hpp | 29 inst/include/armadillo_bits/fn_find.hpp | 4 inst/include/armadillo_bits/fn_kmeans.hpp | 2 inst/include/armadillo_bits/fn_lu.hpp | 4 inst/include/armadillo_bits/fn_misc.hpp | 2 inst/include/armadillo_bits/fn_qr.hpp | 6 inst/include/armadillo_bits/fn_randperm.hpp | 4 inst/include/armadillo_bits/fn_sort.hpp | 6 inst/include/armadillo_bits/fn_sort_index.hpp | 4 inst/include/armadillo_bits/fn_strans.hpp | 16 inst/include/armadillo_bits/fn_trans.hpp | 8 inst/include/armadillo_bits/fn_trimat.hpp | 60 inst/include/armadillo_bits/fn_zeros.hpp | 4 inst/include/armadillo_bits/gmm_misc_bones.hpp | 4 inst/include/armadillo_bits/gmm_misc_meat.hpp | 2 inst/include/armadillo_bits/injector_meat.hpp | 6 inst/include/armadillo_bits/memory.hpp | 28 inst/include/armadillo_bits/newarp_SparseGenRealShiftSolve_bones.hpp |only inst/include/armadillo_bits/newarp_SparseGenRealShiftSolve_meat.hpp |only inst/include/armadillo_bits/newarp_SymEigsShiftSolver_bones.hpp |only inst/include/armadillo_bits/newarp_SymEigsShiftSolver_meat.hpp |only inst/include/armadillo_bits/newarp_SymEigsSolver_bones.hpp | 10 inst/include/armadillo_bits/newarp_SymEigsSolver_meat.hpp | 42 inst/include/armadillo_bits/op_dot_bones.hpp | 2 inst/include/armadillo_bits/op_dot_meat.hpp | 3 inst/include/armadillo_bits/op_fft_meat.hpp | 4 inst/include/armadillo_bits/op_find_meat.hpp | 18 inst/include/armadillo_bits/op_hist_meat.hpp | 31 inst/include/armadillo_bits/op_htrans_bones.hpp | 12 inst/include/armadillo_bits/op_htrans_meat.hpp | 3 inst/include/armadillo_bits/op_index_max_meat.hpp | 6 inst/include/armadillo_bits/op_index_min_meat.hpp | 6 inst/include/armadillo_bits/op_max_meat.hpp | 2 inst/include/armadillo_bits/op_median_bones.hpp | 8 inst/include/armadillo_bits/op_median_meat.hpp | 19 inst/include/armadillo_bits/op_min_meat.hpp | 2 inst/include/armadillo_bits/op_princomp_meat.hpp | 10 inst/include/armadillo_bits/op_range_meat.hpp | 2 inst/include/armadillo_bits/op_toeplitz_meat.hpp | 2 inst/include/armadillo_bits/op_vectorise_meat.hpp | 4 inst/include/armadillo_bits/podarray_meat.hpp | 4 inst/include/armadillo_bits/running_stat_vec_meat.hpp | 4 inst/include/armadillo_bits/sp_auxlib_bones.hpp | 134 - inst/include/armadillo_bits/sp_auxlib_meat.hpp | 1270 ++++++++-- inst/include/armadillo_bits/spop_trimat_bones.hpp | 28 inst/include/armadillo_bits/spop_trimat_meat.hpp | 222 + inst/include/armadillo_bits/subview_bones.hpp | 14 inst/include/armadillo_bits/subview_cube_bones.hpp | 13 inst/include/armadillo_bits/subview_cube_meat.hpp | 589 ++-- inst/include/armadillo_bits/subview_elem1_meat.hpp | 2 inst/include/armadillo_bits/subview_meat.hpp | 265 +- inst/include/armadillo_bits/traits.hpp | 18 inst/include/armadillo_bits/translate_superlu.hpp | 72 inst/include/armadillo_bits/unwrap_cube.hpp | 23 107 files changed, 4600 insertions(+), 2276 deletions(-)
Title: Estimate Kinship and FST under Arbitrary Population Structure
Description: Provides functions to estimate the kinship matrix of individuals from a large set of biallelic SNPs, and extract inbreeding coefficients and the generalized FST (Wright's fixation index). Method described in Ochoa and Storey (2021) <doi:10.1371/journal.pgen.1009241>.
Author: Alejandro Ochoa [aut, cre] (<https://orcid.org/0000-0003-4928-3403>),
John D. Storey [aut] (<https://orcid.org/0000-0001-5992-402X>)
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>
Diff between popkin versions 1.3.0 dated 2019-12-17 and 1.3.7 dated 2021-02-09
popkin-1.3.0/popkin/R/get_A.R |only popkin-1.3.0/popkin/R/min_mean_subpops.R |only popkin-1.3.7/popkin/DESCRIPTION | 14 popkin-1.3.7/popkin/MD5 | 84 +- popkin-1.3.7/popkin/NAMESPACE | 2 popkin-1.3.7/popkin/NEWS.md | 41 + popkin-1.3.7/popkin/R/fst.R | 29 popkin-1.3.7/popkin/R/inbr.R | 8 popkin-1.3.7/popkin/R/inbr_diag.R | 14 popkin-1.3.7/popkin/R/mean_kinship.R | 6 popkin-1.3.7/popkin/R/n_eff.R | 42 - popkin-1.3.7/popkin/R/plot_popkin.R | 10 popkin-1.3.7/popkin/R/popkin-package.R | 10 popkin-1.3.7/popkin/R/popkin.R | 91 +- popkin-1.3.7/popkin/R/popkin_A.R |only popkin-1.3.7/popkin/R/popkin_A_min_subpops.R |only popkin-1.3.7/popkin/R/pwfst.R | 12 popkin-1.3.7/popkin/R/rescale_popkin.R | 23 popkin-1.3.7/popkin/R/solve_m_mem_lim.R | 4 popkin-1.3.7/popkin/R/validate_kinship.R | 34 popkin-1.3.7/popkin/R/weights_subpops.R | 6 popkin-1.3.7/popkin/README.md | 7 popkin-1.3.7/popkin/build/vignette.rds |binary popkin-1.3.7/popkin/inst/doc/popkin.Rmd | 9 popkin-1.3.7/popkin/inst/doc/popkin.html | 489 +++++++------ popkin-1.3.7/popkin/man/fst.Rd | 14 popkin-1.3.7/popkin/man/inbr.Rd | 8 popkin-1.3.7/popkin/man/inbr_diag.Rd | 10 popkin-1.3.7/popkin/man/mean_kinship.Rd | 4 popkin-1.3.7/popkin/man/n_eff.Rd | 40 - popkin-1.3.7/popkin/man/plot_popkin.Rd | 5 popkin-1.3.7/popkin/man/popkin-package.Rd | 10 popkin-1.3.7/popkin/man/popkin.Rd | 50 - popkin-1.3.7/popkin/man/popkin_A.Rd |only popkin-1.3.7/popkin/man/popkin_A_min_subpops.Rd |only popkin-1.3.7/popkin/man/pwfst.Rd | 12 popkin-1.3.7/popkin/man/rescale_popkin.Rd | 20 popkin-1.3.7/popkin/man/validate_kinship.Rd | 15 popkin-1.3.7/popkin/man/weights_subpops.Rd | 6 popkin-1.3.7/popkin/tests/testthat/Xs.RData |binary popkin-1.3.7/popkin/tests/testthat/make_data.R | 13 popkin-1.3.7/popkin/tests/testthat/test_popkin.R | 139 +++ popkin-1.3.7/popkin/tests/testthat/test_popkin_BEDMatrix.R | 6 popkin-1.3.7/popkin/tests/testthat/test_popkin_fn.R | 15 popkin-1.3.7/popkin/vignettes/popkin.Rmd | 9 popkin-1.3.7/popkin/vignettes/popkin.bib | 38 - 46 files changed, 856 insertions(+), 493 deletions(-)
Title: Generalized Dynamic Principal Components
Description: Functions to compute the Generalized Dynamic Principal Components
introduced in Peña and Yohai (2016) <DOI:10.1080/01621459.2015.1072542>. The implementation
includes an automatic procedure proposed in Peña, Smucler and Yohai (2020) <DOI:10.18637/jss.v092.c02>
for the identification of both the number of lags to be used
in the generalized dynamic principal components as well as the number of components required
for a given reconstruction accuracy.
Author: Daniel Peña <daniel.pena@uc3m.es>,
Ezequiel Smucler <ezequiels.90@gmail.com>,
Victor Yohai <vyohai@dm.uba.ar>
Maintainer: Ezequiel Smucler <ezequiels.90@gmail.com>
Diff between gdpc versions 1.1.1 dated 2020-02-23 and 1.1.2 dated 2021-02-09
DESCRIPTION | 11 ++++++----- MD5 | 21 +++++++++++++++++---- NEWS | 6 ++++++ build |only inst/doc |only man/auto.gdpc.Rd | 2 +- man/gdpc-package.Rd | 6 +++--- vignettes |only 8 files changed, 33 insertions(+), 13 deletions(-)
Title: Beta Regression
Description: Beta regression for modeling beta-distributed dependent variables, e.g., rates and proportions.
In addition to maximum likelihood regression (for both mean and precision of a beta-distributed
response), bias-corrected and bias-reduced estimation as well as finite mixture models and
recursive partitioning for beta regressions are provided.
Author: Achim Zeileis [aut, cre],
Francisco Cribari-Neto [aut],
Bettina Gruen [aut],
Ioannis Kosmidis [aut],
Alexandre B. Simas [ctb] (earlier version by),
Andrea V. Rocha [ctb] (earlier version by)
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>
Diff between betareg versions 3.1-3 dated 2020-02-03 and 3.1-4 dated 2021-02-09
DESCRIPTION | 8 ++--- MD5 | 52 +++++++++++++++++------------------ NEWS | 6 ++++ R/betatree.R | 4 +- build/partial.rdb |binary build/vignette.rds |binary data/CarTask.rda |binary data/FoodExpenditure.rda |binary data/GasolineYield.rda |binary data/ImpreciseTask.rda |binary data/MockJurors.rda |binary data/ReadingSkills.rda |binary data/StressAnxiety.rda |binary data/WeatherTask.rda |binary inst/CITATION | 69 +++++++++++++++++++---------------------------- inst/doc/betareg-ext.pdf |binary inst/doc/betareg.pdf |binary man/FoodExpenditure.Rd | 2 - man/GasolineYield.Rd | 2 - man/ReadingSkills.Rd | 4 +- man/betamix.Rd | 8 ++--- man/betareg.Rd | 4 +- man/betatree.Rd | 4 +- man/gleverage.Rd | 2 - man/plot.betareg.Rd | 2 - man/residuals.betareg.Rd | 2 - man/summary.betareg.Rd | 2 - 27 files changed, 83 insertions(+), 88 deletions(-)
Title: The Time Series Modeling Companion to 'healthyR'
Description: Hospital time series data analysis workflow tools, modeling, and automations.
This library provides many useful tools to review common administrative time
series hospital data. Some of these include average length of stay, and
readmission rates. The aim is to provide a simple and consistent verb
framework that takes the guesswork out of everything.
Author: Steven Sanderson [aut, cre],
Steven Sanderson [cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>
Diff between healthyR.ts versions 0.1.0 dated 2021-01-22 and 0.1.1 dated 2021-02-09
DESCRIPTION | 11 ++++--- MD5 | 16 +++++------ NEWS.md | 5 +++ README.md | 21 ++++++++------ inst/doc/getting-started.html | 26 +++++++++--------- man/figures/README-ts_random_walk_ggplot_layers-1.png |binary man/figures/README-unnamed-chunk-2-1.png |binary man/pipe.Rd | 3 ++ man/tidyeval.Rd | 3 ++ 9 files changed, 50 insertions(+), 35 deletions(-)
Title: Bayesian Estimation of (Sparse) Latent Factor Stochastic
Volatility Models
Description: Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility models with interweaving <doi:10.1080/10618600.2017.1322091>. Sparsity can be achieved through the usage of Normal-Gamma priors on the factor loading matrix <doi:10.1016/j.jeconom.2018.11.007>.
Author: Gregor Kastner [aut, cre] (<https://orcid.org/0000-0002-8237-8271>),
Darjus Hosszejni [ctb] (<https://orcid.org/0000-0002-3803-691X>)
Maintainer: Gregor Kastner <gregor.kastner@aau.at>
Diff between factorstochvol versions 0.10.1 dated 2020-11-13 and 0.10.2 dated 2021-02-09
factorstochvol-0.10.1/factorstochvol/inst/doc/paper.R |only factorstochvol-0.10.1/factorstochvol/inst/doc/paper.Rnw |only factorstochvol-0.10.1/factorstochvol/vignettes/paper.Rnw |only factorstochvol-0.10.2/factorstochvol/DESCRIPTION | 9 + factorstochvol-0.10.2/factorstochvol/MD5 | 47 ++++++---- factorstochvol-0.10.2/factorstochvol/NEWS | 5 + factorstochvol-0.10.2/factorstochvol/R/factorstochvol-package.R | 6 - factorstochvol-0.10.2/factorstochvol/R/utilities_other.R | 10 -- factorstochvol-0.10.2/factorstochvol/R/wrappers.R | 8 - factorstochvol-0.10.2/factorstochvol/build/partial.rdb |only factorstochvol-0.10.2/factorstochvol/build/vignette.rds |binary factorstochvol-0.10.2/factorstochvol/inst/CITATION | 12 +- factorstochvol-0.10.2/factorstochvol/inst/doc/paper.Rtex |only factorstochvol-0.10.2/factorstochvol/inst/doc/paper.pdf |binary factorstochvol-0.10.2/factorstochvol/man/factorstochvol-package.Rd | 6 - factorstochvol-0.10.2/factorstochvol/man/fsvsample.Rd | 8 - factorstochvol-0.10.2/factorstochvol/man/logret.Rd | 4 factorstochvol-0.10.2/factorstochvol/src/sampler.cpp | 11 -- factorstochvol-0.10.2/factorstochvol/vignettes/Figures |only factorstochvol-0.10.2/factorstochvol/vignettes/paper.Rtex |only factorstochvol-0.10.2/factorstochvol/vignettes/ref.bib | 25 +++-- 21 files changed, 81 insertions(+), 70 deletions(-)
More information about factorstochvol at CRAN
Permanent link
Title: Scrape Lake Metadata Tables from Wikipedia
Description: Scrape lake metadata tables from Wikipedia <https://www.wikipedia.org/>.
Author: Joseph Stachelek [aut, cre] (<https://orcid.org/0000-0002-5924-2464>)
Maintainer: Joseph Stachelek <stachel2@msu.edu>
Diff between wikilake versions 0.4 dated 2018-06-07 and 0.5.0 dated 2021-02-09
DESCRIPTION | 12 - MD5 | 47 +++---- NAMESPACE | 5 NEWS.md | 10 + R/clean.R |only R/get.R | 49 ++++++- R/map.R | 12 - R/units.R | 18 ++ R/utils.R | 32 +++++ README.md | 147 +++++++++++++---------- build/vignette.rds |binary data/milakes.rda |binary inst/doc/scrape_michigan_lakes.R | 29 ++-- inst/doc/scrape_michigan_lakes.Rmd | 9 - inst/doc/scrape_michigan_lakes.html | 230 +++++++++++++++++++++++------------- man/lake_clean.Rd |only man/lake_wiki.Rd | 9 + man/map_lake_wiki.Rd | 4 man/milakes.Rd | 6 man/parse_unit_brackets.Rd |only tests/testthat/test-lake_wiki.R | 21 +++ tools/images/mapping-1.png |binary tools/images/mapping2-1.png |binary tools/images/mapping3-1.png |binary tools/images/worldmapping-1.png |binary vignettes/scrape_michigan_lakes.Rmd | 9 - 26 files changed, 422 insertions(+), 227 deletions(-)
Title: Phenotypic Index Measures for Oak Decline Severity
Description: Oak declines are complex disease syndromes and consist of many visual indicators that include aspects of tree size, crown condition and trunk condition. This can cause difficulty in the manual classification of symptomatic and non-symptomatic trees from what is in reality a broad spectrum of oak tree health condition. Two phenotypic oak decline indexes have been developed to quantitatively describe and differentiate oak decline syndromes in Quercus robur. This package provides a toolkit to generate these decline indexes from phenotypic descriptors using the machine learning algorithm random forest. The methodology for generating these indexes is outlined in Finch et al. (2121) <doi:10.1016/j.foreco.2021.118948>.
Author: Jasen Finch [aut, cre] (<https://orcid.org/0000-0002-6070-7476>)
Maintainer: Jasen Finch <jsf9@aber.ac.uk>
Diff between pdi versions 0.4.1 dated 2020-08-19 and 0.4.2 dated 2021-02-09
DESCRIPTION | 8 MD5 | 13 - NEWS.md |only README.md | 29 ++ build/vignette.rds |binary inst/doc/pdi-example.Rmd | 4 inst/doc/pdi-example.html | 452 ++++++++++++++-------------------------------- vignettes/pdi-example.Rmd | 4 8 files changed, 188 insertions(+), 322 deletions(-)
Title: Simulated Predicted Probabilities for Multinomial Logit Models
Description: Functions to easily return simulated predicted probabilities and
first differences for multinomial logit models. It takes a specified
scenario and a multinomial model to predict probabilities with a set of
coefficients, drawn from a simulated sampling distribution. The simulated
predictions allow for meaningful plots with means and confidence intervals.
The methodological approach is based on the principles laid out by King,
Tomz, and Wittenberg (2000) <doi:10.2307/2669316> and Hanmer and Ozan Kalkan
(2016) <doi:10.1111/j.1540-5907.2012.00602.x>.
Author: Manuel Neumann [aut, cre] (<https://orcid.org/0000-0002-7953-3939>)
Maintainer: Manuel Neumann <manuel.neumann@mzes.uni-mannheim.de>
Diff between MNLpred versions 0.0.4 dated 2020-09-02 and 0.0.5 dated 2021-02-09
DESCRIPTION | 8 MD5 | 48 - NAMESPACE | 22 NEWS.md | 7 R/gles-data.R | 66 +- R/mnl_fd2_ova.R | 40 + R/mnl_fd_ova.R | 62 +- R/mnl_pred_ova.R | 92 ++- README.md | 75 +- build/vignette.rds |binary inst/CITATION | 4 inst/doc/OVA_Predictions_For_MNL.R | 10 inst/doc/OVA_Predictions_For_MNL.Rmd | 18 inst/doc/OVA_Predictions_For_MNL.html | 610 ++++++++---------------- man/figures/README-first_differences_plot-1.png |binary man/figures/README-prediction_plot1-1.png |binary man/figures/README-prediction_plot2-1.png |binary man/figures/README-static_fd_plot-1.png |binary man/mnl_fd2_ova.Rd | 9 man/mnl_fd_ova.Rd | 21 man/mnl_pred_ova.Rd | 25 tests/testthat.R | 8 tests/testthat/test_inputvariants.R | 22 vignettes/OVA_Predictions_For_MNL.Rmd | 18 vignettes/bibliography.bib | 76 +- 25 files changed, 585 insertions(+), 656 deletions(-)
Title: MultiDimensional Feature Selection
Description: Functions for MultiDimensional Feature Selection (MDFS):
calculating multidimensional information gains, scoring variables,
finding important variables, plotting selection results.
This package includes an optional CUDA implementation that speeds up
information gain calculation using NVIDIA GPGPUs.
R. Piliszek et al. (2019) <doi:10.32614/RJ-2019-019>.
Author: Radosław Piliszek [aut, cre],
Krzysztof Mnich [aut],
Paweł Tabaszewski [aut],
Szymon Migacz [aut],
Andrzej Sułecki [aut],
Witold Remigiusz Rudnicki [aut]
Maintainer: Radosław Piliszek <r.piliszek@uwb.edu.pl>
Diff between MDFS versions 1.1.1 dated 2021-01-21 and 1.2.0 dated 2021-02-09
DESCRIPTION | 9 MD5 | 72 +- NAMESPACE | 40 - NEWS | 143 ++-- R/information_gain.R | 886 +++++++++++++-------------- R/main.R | 182 ++--- R/p_value.R | 742 +++++++++++----------- R/utils.R | 54 - cleanup.win | 10 man/AddContrastVariables.Rd | 54 - man/ComputeInterestingTuples.Rd | 146 ++-- man/ComputeMaxInfoGains.Rd | 136 ++-- man/ComputePValue.Rd | 160 ++-- man/Discretize.Rd | 60 - man/MDFS.Rd | 144 ++-- man/RelevantVariables.MDFS.Rd | 54 - man/RelevantVariables.Rd | 38 - man/as.data.frame.MDFS.Rd | 38 - man/madelon.Rd | 68 +- man/plot.MDFS.Rd | 36 - src/MDFS-win.def | 6 src/Makevars.cuda.in | 32 src/cpu/common.cpp | 56 + src/cpu/common.h | 7 src/cpu/mdfs.h | 11 src/gpu/kernels.cu | 214 +++--- src/gpu/kernels2D.cuh | 1302 ++++++++++++++++++++-------------------- src/gpu/kernels3D.cuh | 1176 ++++++++++++++++++------------------ src/gpu/kernels4D.cuh | 1204 ++++++++++++++++++------------------ src/gpu/kernels5D.cuh | 1298 +++++++++++++++++++-------------------- src/gpu/splitkernel.cuh | 926 ++++++++++++++-------------- src/gpu/tableskernel.cuh | 340 +++++----- src/gpu/utils.cuh | 28 src/r_init.cpp | 2 src/r_interface.cpp | 46 - src/r_interface.h | 3 tests/simple_run.R | 10 37 files changed, 4929 insertions(+), 4804 deletions(-)
Title: Graph Signal Processing
Description: Provides the standard operations for signal processing on graphs:
graph Fourier transform, spectral graph wavelet transform,
visualization tools. It also implements a data driven method
for graph signal denoising/regression, for details see
De Loynes, Navarro, Olivier (2019) <arxiv:1906.01882>.
The package also provides an interface to the SuiteSparse Matrix Collection,
<https://sparse.tamu.edu/>, a large and widely used set of sparse matrix
benchmarks collected from a wide range of applications.
Author: Fabien Navarro [aut, cre],
Basile De Loynes [aut],
Baptiste Olivier [aut]
Maintainer: Fabien Navarro <fabien.navarro@math.cnrs.fr>
Diff between gasper versions 1.0.1 dated 2020-08-03 and 1.1.0 dated 2021-02-09
DESCRIPTION | 13 +++- MD5 | 103 +++++++++++++++++++++---------------- NAMESPACE | 24 ++++++++ NEWS.md | 35 ++++++++++++ R/GVN.R | 5 + R/HPFVN.R |only R/RcppExports.R | 7 -- R/SNR.R |only R/SURE_MSEthresh.R | 114 ++++++++++++++++++++++++++++------------- R/SUREthresh.R | 100 ++++++++++++++++++++++++------------ R/adjacency_mat.R | 3 - R/analysis.R | 1 R/download_graph.R | 62 ++++++++++++++++++---- R/eigensort.R | 5 + R/forward_sgwt.R |only R/full.R | 22 +++++--- R/fullup.R | 9 ++- R/inverse_sgwt.R |only R/laplacian_mat.R | 14 ++++- R/plot_filter.R |only R/plot_graph.R | 5 + R/plot_signal.R | 5 + R/randsignal.R | 39 ++++++++++---- R/smoothmodulus.R | 4 - R/swissroll.R | 4 - R/synthesis.R | 3 - R/tight_frame.R | 36 +------------ R/zetav.R |only inst/CITATION |only inst/doc/gasper_vignette.R | 77 +++++++++++++++++----------- inst/doc/gasper_vignette.pdf |binary inst/doc/gasper_vignette.rmd | 115 ++++++++++++++++++++++++++++++------------ man/GVN.Rd | 2 man/HPFVN.Rd |only man/SNR.Rd |only man/SURE_MSEthresh.Rd | 7 +- man/SUREthresh.Rd | 7 +- man/adjacency_mat.Rd | 2 man/analysis.Rd | 3 + man/download_graph.Rd | 7 +- man/eigendec.Rd | 9 +-- man/eigensort.Rd | 2 man/forward_sgwt.Rd |only man/full.Rd | 3 + man/fullup.Rd | 2 man/gasper-package.Rd | 16 +++++ man/inverse_sgwt.Rd |only man/laplacian_mat.Rd | 3 + man/plot_filter.Rd |only man/randsignal.Rd | 8 +- man/smoothmodulus.Rd | 4 - man/swissroll.Rd | 1 man/synthesis.Rd | 5 + man/tight_frame.Rd | 8 +- man/zetav.Rd |only src/eigendec.cpp | 7 -- vignettes/gasper_vignette.rmd | 115 ++++++++++++++++++++++++++++++------------ vignettes/references.bib | 25 +++++++-- vignettes/template-latex.tex | 1 59 files changed, 710 insertions(+), 332 deletions(-)
Title: Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index
Scores
Description: EQ-5D is a popular health related quality of life instrument used
in the clinical and economic evaluation of health care. Developed by the
EuroQol group <https://euroqol.org/>, the instrument consists of two
components: health state description and evaluation. For the description
component a subject self-rates their health in terms of five dimensions;
mobility, self-care, usual activities, pain/discomfort, and
anxiety/depression using either a three-level (EQ-5D-3L,
<https://euroqol.org/eq-5d-instruments/eq-5d-3l-about/>) or a five-level
(EQ-5D-5L, <https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/>)
scale. Frequently the scores on these five dimensions are converted to a
single utility index using country specific value sets, which can be used
in the clinical and economic evaluation of health care as well as in
population health surveys. The eq5d package provides methods to calculate
index scores from a subject's dimension scores. 26 TTO and 11 VAS EQ-5D-3L
value sets including those for countries in Szende et al (2007)
<doi:10.1007/1-4020-5511-0> and Szende et al (2014)
<doi:10.1007/978-94-007-7596-1>, 26 EQ-5D-5L EQ-VT value sets from the
EuroQol website, and the EQ-5D-5L crosswalk value sets developed by
van Hout et al. (2012) <doi:10.1016/j.jval.2012.02.008> are included.
Methods are also included for the analysis of EQ-5D profiles along with a
shiny web tool to enable the calculation, visualisation and automated
statistical analysis of EQ-5D data via a web browser using EQ-5D dimension
scores stored in CSV or Excel files.
Author: Fraser Morton [aut, cre],
Jagtar Singh Nijjar [aut]
Maintainer: Fraser Morton <fraser.morton@glasgow.ac.uk>
Diff between eq5d versions 0.8.0 dated 2020-11-11 and 0.8.1 dated 2021-02-09
DESCRIPTION | 26 ++++++++++++++------------ MD5 | 24 ++++++++++++------------ NEWS.md | 6 ++++++ R/data.R | 1 + README.md | 38 +++++++++++++++++++------------------- data/tto.RData |binary data/vt.RData |binary inst/doc/eq5d.html | 38 +++++++++++++++++++------------------- man/TTO.Rd | 2 +- man/VT.Rd | 3 ++- man/eq5d-package.Rd | 2 +- tests/testthat/test-eq5d3l.R | 8 ++++++++ tests/testthat/test-eq5d5l.R | 6 ++++++ 13 files changed, 89 insertions(+), 65 deletions(-)
Title: Dose Response for Omics
Description: Several functions are provided for dose-response (or concentration-response) characterization from omics data. 'DRomics' is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of replicates). 'DRomics' provides functions 1) to check, normalize and or transform data, 2) to select monotonic or biphasic significantly responding items (e.g. probes, metabolites), 3) to choose the best-fit model among a predefined family of monotonic and biphasic models to describe each selected item, 4) to derive a benchmark dose or concentration and a typology of response from each fitted curve. In the available version data are supposed to be single-channel microarray data in log2, RNAseq data in raw counts, or already pretreated continuous omics data (such as metabolomic data) in log scale. In order to link responses across biological levels based on a common method, 'DRomics' also handles apical data as long as they are continuous and follow a normal distribution for each dose or concentration, with a common standard error. For further details see Larras et al (2018) <DOI:10.1021/acs.est.8b04752> at <https://hal.archives-ouvertes.fr/hal-02309919>.
Author: Marie-Laure Delignette-Muller [aut],
Elise Billoir [aut],
Floriane Larras [ctb],
Aurelie Siberchicot [aut, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>
Diff between DRomics versions 2.1-3 dated 2020-09-23 and 2.2-0 dated 2021-02-09
DRomics-2.1-3/DRomics/data/Zhou_kidney_tce.rda |only DRomics-2.1-3/DRomics/data/Zhou_liver_pce.rda |only DRomics-2.1-3/DRomics/data/Zhou_liver_tce.rda |only DRomics-2.1-3/DRomics/data/datalist |only DRomics-2.2-0/DRomics/DESCRIPTION |only DRomics-2.2-0/DRomics/MD5 |only DRomics-2.2-0/DRomics/NAMESPACE | 8 +++++--- DRomics-2.2-0/DRomics/R |only DRomics-2.2-0/DRomics/build |only DRomics-2.2-0/DRomics/inst |only DRomics-2.2-0/DRomics/man |only DRomics-2.2-0/DRomics/tests |only DRomics-2.2-0/DRomics/vignettes |only 13 files changed, 5 insertions(+), 3 deletions(-)
Title: Wrapper for the UN OCHA ReliefWeb Disaster Events API
Description: Access and manage the application programming interface (API) of the United Nations Office for the Coordination of Humanitarian Affairs' (OCHA) ReliefWeb disaster events at <https://reliefweb.int/disasters/>. The package requires a minimal number of dependencies. It offers functionality to retrieve a user-defined sample of disaster events from ReliefWeb, providing an easy alternative to scraping the ReliefWeb website. It enables a seamless integration of regular data updates into the research work flow.
Author: Christoph Dworschak [aut, cre]
(<https://orcid.org/0000-0003-0196-9545>)
Maintainer: Christoph Dworschak <c.dworschak@essex.ac.uk>
Diff between disastr.api versions 1.0.3 dated 2021-01-07 and 1.0.4 dated 2021-02-09
DESCRIPTION | 8 ++-- MD5 | 8 ++-- NEWS.md | 5 ++ R/disastr.api.internal.R | 4 +- README.md | 80 +++++++++++++++++++++-------------------------- 5 files changed, 51 insertions(+), 54 deletions(-)
Title: Access, Retrieve, and Work with Canadian Census Data and
Geography
Description: Integrated, convenient, and uniform access to Canadian
Census data and geography retrieved using the 'CensusMapper' API. This package produces analysis-ready
tidy data frames and spatial data in multiple formats, as well as convenience functions
for working with Census variables, variable hierarchies, and region selection. API
keys are freely available with free registration at <https://censusmapper.ca/api>.
Census data and boundary geometries are reproduced and distributed on an "as
is" basis with the permission of Statistics Canada (Statistics Canada 2001; 2006;
2011; 2016).
Author: Jens von Bergmann [aut] (API creator and maintainer),
Dmitry Shkolnik [aut, cre] (Package maintainer, responsible for
correspondence),
Aaron Jacobs [aut]
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>
Diff between cancensus versions 0.4.1 dated 2021-01-27 and 0.4.2 dated 2021-02-09
DESCRIPTION | 6 +++--- MD5 | 16 ++++++++-------- NEWS.md | 10 ++++++++-- R/census_vectors.R | 19 ++++++++++++++----- R/helpers.R | 8 +++++--- README.md | 4 ++-- inst/CITATION | 4 ++-- inst/doc/Making_maps_with_cancensus.html | 12 ++++++------ man/child_census_vectors.Rd | 22 +++++++++++++++++----- 9 files changed, 65 insertions(+), 36 deletions(-)
Title: Multivariate Multiscale Spatial Analysis
Description: Tools for the multiscale spatial analysis of multivariate data.
Several methods are based on the use of a spatial weighting matrix and its
eigenvector decomposition (Moran's Eigenvectors Maps, MEM).
Several approaches are described in the review Dray et al (2012)
<doi:10.1890/11-1183.1>.
Author: Stéphane Dray, David Bauman, Guillaume Blanchet, Daniel Borcard,
Sylvie Clappe, Guillaume Guenard, Thibaut Jombart, Guillaume Larocque,
Pierre Legendre, Naima Madi, Helene H Wagner
Maintainer: Stéphane Dray <stephane.dray@univ-lyon1.fr>
Diff between adespatial versions 0.3-8 dated 2020-02-06 and 0.3-10 dated 2021-02-09
DESCRIPTION | 20 - MD5 | 108 +++--- R/Tiahura.R |only R/WRperiodogram.R | 98 ++++-- R/constr.hclust.R | 131 +++++--- R/dbmem.R | 12 R/ortho.AIC.R | 2 R/plot.constr.hclust.R | 63 ++-- build/vignette.rds |binary data/Tiahura.rda |only inst/doc/tutorial.html | 446 ++++++++++++++-------------- man/Cperiodogram.Rd | 3 man/LCBD.comp.Rd | 10 man/ScotchWhiskey.Rd | 6 man/TBI.Rd | 17 - man/Tiahura.Rd |only man/WRperiodogram.Rd | 104 ++++-- man/aem.Rd | 9 man/aem.build.binary.Rd | 12 man/aem.weight.edges.Rd | 29 + man/bacProdxy.Rd | 4 man/beta.div.Rd | 12 man/chooseCN.Rd | 16 - man/constr.hclust-class.Rd | 6 man/constr.hclust.Rd | 96 +++--- man/dbmem.Rd | 9 man/dist.ldc.Rd | 3 man/envspace.test.Rd | 15 man/figures |only man/forward.sel.Rd | 17 - man/forward.sel.par.Rd | 14 man/listw.candidates.Rd | 13 man/listw.select.Rd | 16 - man/mastigouche.Rd | 6 man/mem.Rd | 21 - man/mem.select.Rd | 15 man/mfpa.Rd | 11 man/moranNP.randtest.Rd | 9 man/mspa.Rd | 24 + man/msr.4thcorner.Rd | 10 man/msr.Rd | 13 man/msr.mantelrtest.Rd | 9 man/msr.varipart.Rd | 9 man/multispati.Rd | 3 man/ortho.AIC.Rd | 2 man/orthobasis.poly.Rd | 3 man/plot.TBI.Rd | 24 + man/plot.constr.hclust.Rd | 40 +- man/plot.orthobasisSp.Rd | 3 man/scalogram.Rd | 9 man/stimodels.Rd | 29 + man/test.W.Rd | 10 man/tpaired.randtest.Rd | 9 man/trichoptera.Rd | 4 src/constr.hclust.c | 700 ++++++++++++++++++++++++++++++++++++++------- src/constr.hclust.h | 125 ++++++-- src/init.c | 2 57 files changed, 1683 insertions(+), 698 deletions(-)
Title: The Official SolveBio API Client
Description: R language bindings for SolveBio's API.
SolveBio is a biomedical knowledge hub that enables life science
organizations to collect and harmonize the complex, disparate
"multi-omic" data essential for today's R&D and BI needs.
For more information, visit <https://www.solvebio.com>.
Author: David Caplan
Maintainer: David Caplan <dcaplan@solvebio.com>
Diff between solvebio versions 2.9.0 dated 2020-08-25 and 2.10.0 dated 2021-02-09
DESCRIPTION | 8 - MD5 | 19 ++-- NAMESPACE | 3 NEWS.md | 6 + R/dataset.R | 9 +- R/object.R | 139 +++++++++++++++++++++++++++++++ R/utils.R | 9 +- README.md | 228 --------------------------------------------------- man/Dataset.data.Rd | 4 man/Object.data.Rd |only man/Object.fields.Rd |only man/Object.query.Rd |only 12 files changed, 180 insertions(+), 245 deletions(-)
Title: Electrochemical Reactions Simulation
Description: Digital simulation of electrochemical processes.
Each function allows for implicit and explicit solution of the differential equation using methods like Euler, Backwards implicit, Runge Kutta 4, Crank Nicholson and Backward differentiation formula as well as different number of points for derivative approximation. Several electrochemical processes can be simulated such as: Chronoamperometry, Potential Step, Linear Sweep, Cyclic Voltammetry, Cyclic Voltammetry with electrochemical reaction followed by chemical reaction (EC mechanism) and CV with two following electrochemical reaction (EE mechanism). In update 1.1.0 has been added a general purpose CV function that allow to simulate up to 4 EE mechanism combined with chemical reaction for each species.Update 1.2.0 improved the accuracy of the measurements and allow personalized data resolution for simulation.
Bibliography regarding this methods can be found in the following texts.
Dieter Britz, Jorg Strutwolf (2016) <ISBN:978-3-319-30292-8>.
Allen J. Bard, Larry R. Faulkner (2000) <ISBN:978-0-471-04372-0>.
Author: Federico Maria Vivaldi [aut, cre]
Maintainer: Federico Maria Vivaldi <federico-vivaldi@virgilio.it>
Diff between EleChemr versions 1.1.0 dated 2019-05-15 and 1.2.0 dated 2021-02-09
DESCRIPTION | 10 MD5 | 24 R/Derivative.R | 878 ++++---- R/EleChemr.R | 6040 ++++++++++++++++++++++++++++---------------------------- man/CV.Rd | 40 man/CVEC.Rd | 43 man/CVEE.Rd | 54 man/ChronAmp.Rd | 26 man/Derv.Rd | 10 man/Gen_CV.Rd | 94 man/LinSwp.Rd | 40 man/ParCall.Rd | 42 man/PotStep.Rd | 29 13 files changed, 3754 insertions(+), 3576 deletions(-)
Title: Analyze Experimental High-Throughput (Omics) Data
Description: The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions.
Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc.
Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM) for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates).
Other functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc.
Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values.
Many times large experimental datasets need some additional filtering, adequate functions are provided.
Batch reading (or writing) of sets of files and combining data to arrays is supported, too.
Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>
Diff between wrMisc versions 1.5.1 dated 2021-01-13 and 1.5.2 dated 2021-02-09
DESCRIPTION | 10 MD5 | 26 - NAMESPACE | 2 R/linModelSelect.R | 83 ++-- R/matchSampToPairw.R |only R/pVal2lfdr.R | 2 R/rowGrpNA.R |only R/stableMode.R | 155 ++++--- inst/doc/wrMiscVignette1.R | 41 +- inst/doc/wrMiscVignette1.Rmd | 100 ++++- inst/doc/wrMiscVignette1.html | 826 ++++++++++++++++++++++-------------------- man/linModelSelect.Rd | 15 man/matchSampToPairw.Rd |only man/rowGrpNA.Rd |only man/stableMode.Rd | 38 + vignettes/wrMiscVignette1.Rmd | 100 ++++- 16 files changed, 837 insertions(+), 561 deletions(-)
Title: System Native Font Finding
Description: Provides system native access to the font catalogue. As font
handling varies between systems it is difficult to correctly locate
installed fonts across different operating systems. The 'systemfonts'
package provides bindings to the native libraries on Windows, macOS and
Linux for finding font files that can then be used further by e.g. graphic
devices. The main use is intended to be from compiled code but 'systemfonts'
also provides access from R.
Author: Thomas Lin Pedersen [aut, cre]
(<https://orcid.org/0000-0002-5147-4711>),
Jeroen Ooms [aut] (<https://orcid.org/0000-0002-4035-0289>),
Devon Govett [aut] (Author of font-manager),
RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@rstudio.com>
Diff between systemfonts versions 1.0.0 dated 2021-02-01 and 1.0.1 dated 2021-02-09
DESCRIPTION | 6 +-- MD5 | 10 +++--- NEWS.md | 6 +++ inst/doc/c_interface.html | 63 ----------------------------------------- src/mac/FontManagerMac.mm | 8 +++-- src/win/FontManagerWindows.cpp | 3 - 6 files changed, 20 insertions(+), 76 deletions(-)
Title: Single-Index Models with Multiple-Links
Description: A major challenge in estimating treatment decision rules from a randomized clinical trial dataset with covariates measured at baseline lies in detecting relatively small treatment effect modification-related variability (i.e., the treatment-by-covariates interaction effects on treatment outcomes) against a relatively large non-treatment-related variability (i.e., the main effects of covariates on treatment outcomes). The class of Single-Index Models with Multiple-Links is a novel single-index model specifically designed to estimate a single-index (a linear combination) of the covariates associated with the treatment effect modification-related variability, while allowing a nonlinear association with the treatment outcomes via flexible link functions. The models provide a flexible regression approach to developing treatment decision rules based on patients' data measured at baseline. We refer to Park, Petkova, Tarpey, and Ogden (2020) <doi:10.1016/j.jspi.2019.05.008> and Park, Petkova, Tarpey, and Ogden (2020) <doi:10.1111/biom.13320> (that allows an unspecified X main effect) for detail of the method. The main function of this package is simml().
Author: Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden
Maintainer: Hyung Park <parkh15@nyu.edu>
Diff between simml versions 0.1.0 dated 2019-05-24 and 0.2.0 dated 2021-02-09
simml-0.1.0/simml/R/simml-main.R |only simml-0.2.0/simml/DESCRIPTION | 12 - simml-0.2.0/simml/MD5 | 18 +- simml-0.2.0/simml/NAMESPACE | 3 simml-0.2.0/simml/R/hello.R |only simml-0.2.0/simml/R/simml.main.R |only simml-0.2.0/simml/man/der.link.Rd | 8 simml-0.2.0/simml/man/fit.simml.Rd | 67 +++++--- simml-0.2.0/simml/man/generate.data.Rd | 20 +- simml-0.2.0/simml/man/ordinal.data.Rd |only simml-0.2.0/simml/man/pred.simml.Rd | 15 + simml-0.2.0/simml/man/simml.Rd | 266 +++++++++++++++++++-------------- 12 files changed, 245 insertions(+), 164 deletions(-)
Title: ROBustness in Network
Description: Assesses the robustness of the community structure of a network found by one or more community detection algorithm to give indications about their reliability. It detects if the community structure found by a set of algorithms is statistically significant and compares the different selected detection algorithms on the same network. robin helps to choose among different community detection algorithms the one that better fits the network of interest. Reference in Policastro V., Righelli D., Carissimo A., Cutillo L., De Feis I. (2021) <arXiv:2102.03106>.
Author: Valeria Policastro [aut, cre],
Dario Righelli [aut],
Luisa Cutillo [aut],
Italia De Feis [aut],
Annamaria Carissimo [aut]
Maintainer: Valeria Policastro <valeria.policastro@gmail.com>
Diff between robin versions 1.0.2 dated 2020-10-30 and 1.0.3 dated 2021-02-09
DESCRIPTION | 8 +- MD5 | 18 ++-- R/ROBIN.R | 64 ++++++++++------ README.md | 2 inst/NEWS | 2 inst/doc/robin.R | 10 ++ inst/doc/robin.Rmd | 25 +++++- inst/doc/robin.html | 196 ++++++++++++++++++++++------------------------------ man/prepGraph.Rd | 8 ++ vignettes/robin.Rmd | 25 +++++- 10 files changed, 200 insertions(+), 158 deletions(-)
Title: Ridge-Type Penalized Estimation of a Potpourri of Models
Description: The name of the package is derived from the French, 'pour' ridge, and provides functionality for ridge-type estimation of a potpourri of models. Currently, this estimation concerns that of various Gaussian graphical models from different study designs. Among others it considers the regular Gaussian graphical model and a mixture of such models. The porridge-package implements the estimation of the former either from i) data with replicated observations by penalized loglikelihood maximization using the regular ridge penalty on the parameters (van Wieringen, Chen, 2019) or ii) from non-replicated data by means of either a ridge estimator with multiple shrinkage targets (as presented in van Wieringen et al. 2020, <doi:10.1016/j.jmva.2020.104621>) or the generalized ridge estimator that allows for both the inclusion of quantitative and qualitative prior information on the precision matrix via element-wise penalization and shrinkage (van Wieringen, 2019, <doi:10.1080/10618600.2019.1604374>). Additionally, the porridge-package facilitates the ridge penalized estimation of a mixture of Gaussian graphical models (Aflakparast et al., 2018, <doi:10.1002/bimj.201700102>).
Author: Wessel N. van Wieringen [aut, cre],
Mehran Aflakparast [ctb] (part of the R-code of the mixture
functionality)
Maintainer: Wessel N. van Wieringen <w.vanwieringen@vumc.nl>
Diff between porridge versions 0.1.1 dated 2021-01-11 and 0.2.0 dated 2021-02-09
DESCRIPTION | 10 +++++----- MD5 | 11 ++++++++--- R/ridgeGLMandCo.R |only inst/NEWS.Rd | 7 ++++++- man/optPenaltyGLM.kCVauto.Rd |only man/optPenaltyGLMmultiT.kCVauto.Rd |only man/porridge-package.Rd | 14 ++++++++++---- man/ridgeGLM.Rd |only man/ridgeGLMmultiT.Rd |only 9 files changed, 29 insertions(+), 13 deletions(-)
Title: Bayesian Reconstruction of Disease Outbreaks by Combining
Epidemiologic and Genomic Data
Description: Bayesian reconstruction of disease outbreaks using epidemiological
and genetic information. Jombart T, Cori A, Didelot X, Cauchemez S, Fraser
C and Ferguson N. 2014. <doi:10.1371/journal.pcbi.1003457>. Campbell, F,
Cori A, Ferguson N, Jombart T. 2019. <doi:10.1371/journal.pcbi.1006930>.
Author: Thibaut Jombart [aut],
Finlay Campbell [aut, cre],
Rich Fitzjohn [aut],
Gerry Tonkin-Hill [ctb],
Kristjan Eldjarn [ctb],
Alexis Robert [ctb]
Maintainer: Finlay Campbell <finlaycampbell93@gmail.com>
Diff between outbreaker2 versions 1.1.1 dated 2020-02-07 and 1.1.2 dated 2021-02-09
outbreaker2-1.1.1/outbreaker2/vignettes/figs-customisation/null_net-2.png |only outbreaker2-1.1.1/outbreaker2/vignettes/figs-introduction/traces-4.png |only outbreaker2-1.1.2/outbreaker2/DESCRIPTION | 14 outbreaker2-1.1.2/outbreaker2/MD5 | 230 outbreaker2-1.1.2/outbreaker2/NAMESPACE | 97 outbreaker2-1.1.2/outbreaker2/NEWS.md | 147 outbreaker2-1.1.2/outbreaker2/R/RcppExports.R | 230 outbreaker2-1.1.2/outbreaker2/R/bind_moves.R | 272 outbreaker2-1.1.2/outbreaker2/R/bind_to_function.R | 244 outbreaker2-1.1.2/outbreaker2/R/create_config.R | 1491 - outbreaker2-1.1.2/outbreaker2/R/create_param.R | 318 outbreaker2-1.1.2/outbreaker2/R/custom_likelihoods.R | 417 outbreaker2-1.1.2/outbreaker2/R/custom_moves.R | 358 outbreaker2-1.1.2/outbreaker2/R/custom_priors.R | 444 outbreaker2-1.1.2/outbreaker2/R/internals.R | 986 outbreaker2-1.1.2/outbreaker2/R/outbreaker.R | 326 outbreaker2-1.1.2/outbreaker2/R/outbreaker_chains_methods.R | 895 outbreaker2-1.1.2/outbreaker2/R/outbreaker_data.R | 499 outbreaker2-1.1.2/outbreaker2/R/outbreaker_find_imports.R | 178 outbreaker2-1.1.2/outbreaker2/R/outbreaker_init_mcmc.R | 56 outbreaker2-1.1.2/outbreaker2/R/outbreaker_mcmc_shape.R | 92 outbreaker2-1.1.2/outbreaker2/R/outbreaker_mcmc_store.R | 78 outbreaker2-1.1.2/outbreaker2/R/outbreaker_move.R | 134 outbreaker2-1.1.2/outbreaker2/R/ref_likelihoods.R | 238 outbreaker2-1.1.2/outbreaker2/R/sim_ctd.R | 188 outbreaker2-1.1.2/outbreaker2/README.md | 206 outbreaker2-1.1.2/outbreaker2/build/vignette.rds |binary outbreaker2-1.1.2/outbreaker2/inst/doc/Rcpp_API.R | 74 outbreaker2-1.1.2/outbreaker2/inst/doc/Rcpp_API.Rmd | 220 outbreaker2-1.1.2/outbreaker2/inst/doc/Rcpp_API.html | 997 outbreaker2-1.1.2/outbreaker2/inst/doc/customisation.R | 706 outbreaker2-1.1.2/outbreaker2/inst/doc/customisation.Rmd | 2 outbreaker2-1.1.2/outbreaker2/inst/doc/customisation.html | 2433 +- outbreaker2-1.1.2/outbreaker2/inst/doc/introduction.R | 260 outbreaker2-1.1.2/outbreaker2/inst/doc/introduction.Rmd | 558 outbreaker2-1.1.2/outbreaker2/inst/doc/introduction.html |11827 +++++----- outbreaker2-1.1.2/outbreaker2/inst/doc/overview.R | 20 outbreaker2-1.1.2/outbreaker2/inst/doc/overview.Rmd | 162 outbreaker2-1.1.2/outbreaker2/inst/doc/overview.html | 797 outbreaker2-1.1.2/outbreaker2/man/bind_to_function.Rd | 56 outbreaker2-1.1.2/outbreaker2/man/create_config.Rd | 333 outbreaker2-1.1.2/outbreaker2/man/create_param.Rd | 225 outbreaker2-1.1.2/outbreaker2/man/custom_likelihoods.Rd | 11 outbreaker2-1.1.2/outbreaker2/man/custom_moves.Rd | 173 outbreaker2-1.1.2/outbreaker2/man/custom_priors.Rd | 232 outbreaker2-1.1.2/outbreaker2/man/fake_outbreak.Rd | 84 outbreaker2-1.1.2/outbreaker2/man/outbreaker.Rd | 180 outbreaker2-1.1.2/outbreaker2/man/outbreaker_chains.Rd | 177 outbreaker2-1.1.2/outbreaker2/man/outbreaker_data.Rd | 116 outbreaker2-1.1.2/outbreaker2/man/sim_ctd.Rd | 84 outbreaker2-1.1.2/outbreaker2/src/likelihoods.cpp | 55 outbreaker2-1.1.2/outbreaker2/src/moves.cpp | 9 outbreaker2-1.1.2/outbreaker2/tests/testthat/test_config.R | 116 outbreaker2-1.1.2/outbreaker2/tests/testthat/test_data.R | 322 outbreaker2-1.1.2/outbreaker2/tests/testthat/test_find_imports.R | 96 outbreaker2-1.1.2/outbreaker2/tests/testthat/test_likelihoods.R | 1227 - outbreaker2-1.1.2/outbreaker2/tests/testthat/test_moves.R | 470 outbreaker2-1.1.2/outbreaker2/tests/testthat/test_non_exported.R | 556 outbreaker2-1.1.2/outbreaker2/tests/testthat/test_outbreaker.R | 885 outbreaker2-1.1.2/outbreaker2/vignettes/Rcpp_API.Rmd | 220 outbreaker2-1.1.2/outbreaker2/vignettes/customisation.Rmd | 2 outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/__packages | 6 outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_new_move_5726c9b3e30924d986e3e44ffd6e0036.RData |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_new_move_5726c9b3e30924d986e3e44ffd6e0036.rdb |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_new_move_5726c9b3e30924d986e3e44ffd6e0036.rdx |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_null_model_d112d898e13cade05279d2d90d34e60f.RData |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_null_model_d112d898e13cade05279d2d90d34e60f.rdb |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_null_model_d112d898e13cade05279d2d90d34e60f.rdx |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_wt_ffbe1bb0ebffddc18bb5d3ae3b1b3a5f.RData |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_wt_ffbe1bb0ebffddc18bb5d3ae3b1b3a5f.rdb |binary outbreaker2-1.1.2/outbreaker2/vignettes/customisation_cache/html/run_wt_ffbe1bb0ebffddc18bb5d3ae3b1b3a5f.rdx |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/f_pi-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/null_net-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/null_trees-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_new_move-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_new_move-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_null_diag-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_null_diag-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_null_model-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_null_model-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_null_model-3.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_null_priors-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_null_priors-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_wt-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_wt-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/res_wt-3.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/run_custom_move_mu-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/run_custom_move_mu-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/run_custom_move_mu-3.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/traces_custom_priors-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/traces_custom_priors-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/traces_custom_priors-3.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/traces_custom_priors-4.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/traces_custom_priors-5.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-customisation/wt_net-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/basic_trace-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/basic_trace_burn-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/config2-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/config2-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/many_plots-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/many_plots-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/many_plots-3.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/many_plots-4.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/many_plots-5.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/traces-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/traces-2.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/traces-3.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/figs-introduction/w-1.png |binary outbreaker2-1.1.2/outbreaker2/vignettes/introduction.Rmd | 558 outbreaker2-1.1.2/outbreaker2/vignettes/introduction_cache/html/__packages | 8 outbreaker2-1.1.2/outbreaker2/vignettes/introduction_cache/html/config2_e0d3ea2635745de041b80aae763904c7.RData |binary outbreaker2-1.1.2/outbreaker2/vignettes/introduction_cache/html/config2_e0d3ea2635745de041b80aae763904c7.rdb |binary outbreaker2-1.1.2/outbreaker2/vignettes/introduction_cache/html/config2_e0d3ea2635745de041b80aae763904c7.rdx |binary outbreaker2-1.1.2/outbreaker2/vignettes/introduction_cache/html/first_run_931e937e4e7a0450deb5a082d5d9b15b.RData |binary outbreaker2-1.1.2/outbreaker2/vignettes/introduction_cache/html/first_run_931e937e4e7a0450deb5a082d5d9b15b.rdb |binary outbreaker2-1.1.2/outbreaker2/vignettes/introduction_cache/html/first_run_931e937e4e7a0450deb5a082d5d9b15b.rdx |binary outbreaker2-1.1.2/outbreaker2/vignettes/overview.Rmd | 162 117 files changed, 16553 insertions(+), 16004 deletions(-)
Title: Simple Interface to 'Microsoft Graph'
Description: A simple interface to the 'Microsoft Graph' API <https://docs.microsoft.com/en-us/graph/overview>. 'Graph' is a comprehensive framework for accessing data in various online Microsoft services. Currently, this package aims to provide an R interface only to the 'Azure Active Directory' part, with a view to supporting interoperability of R and 'Azure': users, groups, registered apps and service principals. However it can be easily extended to cover other services. Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut, cre],
Microsoft [cph]
Maintainer: Hong Ooi <hongooi73@gmail.com>
Diff between AzureGraph versions 1.2.0 dated 2021-01-13 and 1.2.1 dated 2021-02-09
DESCRIPTION | 6 +++--- MD5 | 12 ++++++------ NEWS.md | 6 ++++++ R/format.R | 2 +- R/ms_object.R | 32 ++++++++++++++++++++++++-------- man/graph_login.Rd | 2 +- man/ms_object.Rd | 21 ++++++++++++++++++++- 7 files changed, 61 insertions(+), 20 deletions(-)
Title: Models for Survival Analysis
Description: Implementations of classical and machine learning models for survival analysis, including deep neural networks via 'keras' and 'tensorflow'. Each model includes a separated fit and predict interface with consistent prediction types for predicting risk, survival probabilities, or survival distributions with 'distr6' <https://CRAN.R-project.org/package=distr6>. Models are either implemented from 'Python' via 'reticulate' <https://CRAN.R-project.org/package=reticulate>, from code in GitHub packages, or novel implementations using 'Rcpp' <https://CRAN.R-project.org/package=Rcpp>. Novel machine learning survival models wil be included in the package in near-future updates. Neural networks are implemented from the 'Python' package 'pycox' <https://github.com/havakv/pycox> and are detailed by Kvamme et al. (2019) <https://jmlr.org/papers/v20/18-424.html>. The 'Akritas' estimator is defined in Akritas (1994) <doi:10.1214/aos/1176325630>. 'DNNSurv' is defined in Zhao and Feng (2020) <arXiv:1908.02337>.
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>)
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>
Diff between survivalmodels versions 0.1.5 dated 2021-01-17 and 0.1.6 dated 2021-02-09
DESCRIPTION | 6 +++--- MD5 | 11 ++++++----- NEWS.md | 4 ++++ R/helpers.R | 21 +++++++++++++++++++++ build/partial.rdb |binary man/set_seed.Rd |only tests/testthat/test_helpers.R | 11 +++++++++++ 7 files changed, 45 insertions(+), 8 deletions(-)
More information about survivalmodels at CRAN
Permanent link
Title: Long Term Prediction for Epidemic and Pandemic Data
Description: Implementation of the methodology described in <http://est.ufmg.br/covidlp/home/pt/> which can be
also found in help(models). Implemented models are currently the Poisson distribution. The mean function can be the
basic generalized logistic form, or the seasonal effect which has under- or over-reporting effects in up to three
weekdays, or the two curves form. Bayesian inference is made available through the 'stan' software and its diagnostic
functions pool can be used. Plot methods are implemented to mimic the graphics from the 'shiny' app in the URL using
the 'plotly' library.
Author: Débora de Freitas Magalhães [aut],
Marta Cristina Colozza Bianchi da Costa [aut],
Guido Alberti Moreira [cre, aut]
(<https://orcid.org/0000-0001-7557-0874>),
Thais Pacheco Menezes [aut],
Marcos Oliveira Prates [ctb] (<https://orcid.org/0000-0001-8077-4898>)
Maintainer: Guido Alberti Moreira <guidoalber@gmail.com>
Diff between PandemicLP versions 0.2.0 dated 2020-11-30 and 0.2.1 dated 2021-02-09
PandemicLP-0.2.0/PandemicLP/README.md |only PandemicLP-0.2.1/PandemicLP/DESCRIPTION | 8 PandemicLP-0.2.1/PandemicLP/MD5 | 61 PandemicLP-0.2.1/PandemicLP/NEWS | 10 PandemicLP-0.2.1/PandemicLP/R/load_covid.R | 394 - PandemicLP-0.2.1/PandemicLP/R/models.R | 4 PandemicLP-0.2.1/PandemicLP/R/pandemicData_class.R | 7 PandemicLP-0.2.1/PandemicLP/R/pandemicEstimated_Class.R | 14 PandemicLP-0.2.1/PandemicLP/R/pandemicStats_Class.R | 7 PandemicLP-0.2.1/PandemicLP/R/pandemic_model.R | 29 PandemicLP-0.2.1/PandemicLP/R/pandemic_stats.R | 421 - PandemicLP-0.2.1/PandemicLP/R/plot.PandemicData.R | 2 PandemicLP-0.2.1/PandemicLP/R/plot.pandemicPredicted.R | 4 PandemicLP-0.2.1/PandemicLP/R/print.pandemicEstimated.R | 8 PandemicLP-0.2.1/PandemicLP/R/print.plottedData.R | 2 PandemicLP-0.2.1/PandemicLP/R/print.summary.pandemicEstimated.R | 12 PandemicLP-0.2.1/PandemicLP/build/vignette.rds |binary PandemicLP-0.2.1/PandemicLP/inst/doc/PandemicLP.html | 2424 ---------- PandemicLP-0.2.1/PandemicLP/inst/doc/PandemicLP_SumRegions.R | 94 PandemicLP-0.2.1/PandemicLP/inst/doc/PandemicLP_SumRegions.Rmd | 108 PandemicLP-0.2.1/PandemicLP/inst/doc/PandemicLP_SumRegions.html | 2337 --------- PandemicLP-0.2.1/PandemicLP/man/load_covid.Rd | 16 PandemicLP-0.2.1/PandemicLP/man/models.Rd | 4 PandemicLP-0.2.1/PandemicLP/man/pandemicData-objects.Rd | 7 PandemicLP-0.2.1/PandemicLP/man/pandemicEstimated-objects.Rd | 14 PandemicLP-0.2.1/PandemicLP/man/pandemicStats-objects.Rd | 7 PandemicLP-0.2.1/PandemicLP/man/pandemic_model.Rd | 29 PandemicLP-0.2.1/PandemicLP/man/pandemic_stats.Rd | 37 PandemicLP-0.2.1/PandemicLP/man/plot.pandemicData.Rd | 2 PandemicLP-0.2.1/PandemicLP/man/print.pandemicEstimated.Rd | 6 PandemicLP-0.2.1/PandemicLP/man/summary.pandemicEstimated.Rd | 2 PandemicLP-0.2.1/PandemicLP/vignettes/PandemicLP_SumRegions.Rmd | 108 32 files changed, 1060 insertions(+), 5118 deletions(-)
Title: Dithionite Scramblase Assay Analysis
Description: The lipid scrambling activity of protein extracts and purified
scramblases is often determined using a fluorescence-based assay involving
many manual steps. flippant offers an integrated solution for the analysis
and publication-grade graphical presentation of dithionite scramblase
assays, as well as a platform for review, dissemination and extension of the
strategies it employs. The package's name derives from a play on the fact
that lipid scrambling is also sometimes referred to as 'flipping'.
The package is originally published as Cotton, R.J., Ploier, B., Goren,
M.A., Menon, A.K., and Graumann, J. (2017). flippant–An R package for the
automated analysis of fluorescence-based scramblase assays. BMC
Bioinformatics 18, 146. <DOI: 10.1186/s12859-017-1542-y>.
Author: Johannes Graumann [cre, aut],
Richard Cotton [ctb]
Maintainer: Johannes Graumann <johannes.graumann@mpi-bn.mpg.de>
Diff between flippant versions 1.5.2 dated 2021-01-29 and 1.5.3 dated 2021-02-09
DESCRIPTION | 6 +++--- MD5 | 4 ++-- R/scramblase_assay_input_validation.R | 9 +++++++-- 3 files changed, 12 insertions(+), 7 deletions(-)
Title: Crowd Sourced System Benchmarks
Description: Benchmark your CPU and compare against other CPUs.
Also provides functions for obtaining system specifications, such as
RAM, CPU type, and R version.
Author: Colin Gillespie [aut, cre] (<https://orcid.org/0000-0003-1787-0275>)
Maintainer: Colin Gillespie <csgillespie@gmail.com>
Diff between benchmarkme versions 1.0.4 dated 2020-05-09 and 1.0.5 dated 2021-02-09
DESCRIPTION | 8 - MD5 | 22 +-- NEWS.md | 5 R/benchmark_parallel.R | 15 ++ R/get_cpu.R | 9 + R/get_ram.R | 10 + README.md | 56 +++----- build/vignette.rds |binary inst/doc/a_introduction.Rmd | 2 inst/doc/a_introduction.html | 242 +++++-------------------------------- tests/testthat/test-benchmark_io.R | 1 vignettes/a_introduction.Rmd | 2 12 files changed, 113 insertions(+), 259 deletions(-)
Title: Miscellaneous Functions for the Analysis of Educational
Assessments
Description: Miscellaneous functions for data cleaning and data analysis of educational assessments. Includes functions for descriptive
analyses, character vector manipulations and weighted statistics. Mainly a lightweight dependency for the packages 'eatRep',
'eatGADS', 'eatPrep' and 'eatModel' (which will be subsequently submitted to 'CRAN').
The function for defining (weighted) contrasts in weighted effect coding refers to
te Grotenhuis et al. (2017) <doi:10.1007/s00038-016-0901-1>.
Functions for weighted statistics refer to
Wolter (2007) <doi:10.1007/978-0-387-35099-8>.
Author: Sebastian Weirich [aut, cre],
Martin Hecht [aut],
Karoline Sachse [aut],
Benjamin Becker [aut],
Nicole Mahler [aut]
Maintainer: Sebastian Weirich <sebastian.weirich@iqb.hu-berlin.de>
Diff between eatTools versions 0.4.0 dated 2021-01-25 and 0.5.0 dated 2021-02-09
DESCRIPTION | 6 - MD5 | 16 +++-- NAMESPACE | 1 NEWS.md | 8 ++ R/recodeLookup.r |only R/wideToLong.r | 23 +++++-- README.md | 3 man/recodeLookup.rd |only man/wideToLong.rd | 104 +++++++++++++++++++-------------- tests/testthat/helper_haven_lookup.RDS |only tests/testthat/test_recodeLookup.R |only 11 files changed, 102 insertions(+), 59 deletions(-)
Title: Automated Retrieval of ACLED Conflict Event Data
Description: Access and manage the application programming interface (API) of the Armed Conflict Location & Event Data Project (ACLED) at <https://acleddata.com/>. The package makes it easy to retrieve a user-defined sample (or all of the available data) of ACLED, enabling a seamless integration of regular data updates into the research work flow. It requires a minimal number of dependencies. See the package's README file for a note on replicability when drawing on ACLED data. When using this package, you acknowledge that you have read ACLED's terms and conditions of use, and that you agree with their attribution requirements.
Author: Christoph Dworschak [aut, cre]
(<https://orcid.org/0000-0003-0196-9545>)
Maintainer: Christoph Dworschak <c.dworschak@essex.ac.uk>
Diff between acled.api versions 1.0.9 dated 2021-01-04 and 1.1.0 dated 2021-02-09
DESCRIPTION | 10 +++++----- MD5 | 10 +++++----- NEWS.md | 4 ++++ R/acled.api.R | 4 ++-- R/acled.api.internal.R | 4 ++-- README.md | 38 +++++++++++++++++++------------------- 6 files changed, 37 insertions(+), 33 deletions(-)
Title: Download and Tidy Time Series Data from the Australian Bureau of
Statistics
Description: Downloads, imports, and tidies time series data from the
Australian Bureau of Statistics <https://www.abs.gov.au/>.
Author: Matt Cowgill [aut, cre] (<https://orcid.org/0000-0003-0422-3300>),
Zoe Meers [aut],
Jaron Lee [aut],
David Diviny [aut],
Hugh Parsonage [ctb]
Maintainer: Matt Cowgill <mattcowgill@gmail.com>
Diff between readabs versions 0.4.6.900 dated 2020-12-15 and 0.4.8 dated 2021-02-09
DESCRIPTION | 12 +- MD5 | 33 +++--- NEWS.md | 7 + R/download_abs.R | 44 ++++----- R/read_abs_local.R | 3 R/read_awe.R | 170 +++++++++++++++++++++++++++++++----- R/read_payrolls.R | 29 +++++- R/sysdata.rda |binary R/tidy_abs.R | 12 ++ README.md | 25 ++++- inst/doc/readabs_vignette.html | 3 man/read_abs_local.Rd | 3 man/read_awe.Rd | 16 ++- tests/testdata/6202021.xls |binary tests/testdata/6302002.xls |only tests/testdata/640101.xls |binary tests/testthat/test-old-functions.R | 5 - tests/testthat/test-read_awe.R | 73 ++++++++++++++- 18 files changed, 345 insertions(+), 90 deletions(-)
Title: Preprocessing Operators and Pipelines for 'mlr3'
Description: Dataflow programming toolkit that enriches 'mlr3' with a diverse
set of pipelining operators ('PipeOps') that can be composed into graphs.
Operations exist for data preprocessing, model fitting, and ensemble
learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can
therefore be resampled, benchmarked, and tuned.
Author: Martin Binder [aut, cre],
Florian Pfisterer [aut] (<https://orcid.org/0000-0001-8867-762X>),
Lennart Schneider [aut] (<https://orcid.org/0000-0003-4152-5308>),
Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>),
Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>),
Susanne Dandl [aut]
Maintainer: Martin Binder <mlr.developer@mb706.com>
Diff between mlr3pipelines versions 0.3.2 dated 2020-12-17 and 0.3.3 dated 2021-02-09
mlr3pipelines-0.3.2/mlr3pipelines/inst |only mlr3pipelines-0.3.3/mlr3pipelines/DESCRIPTION | 10 ++--- mlr3pipelines-0.3.3/mlr3pipelines/MD5 | 18 ++++------ mlr3pipelines-0.3.3/mlr3pipelines/NEWS.md | 5 ++ mlr3pipelines-0.3.3/mlr3pipelines/R/LearnerAvg.R | 5 +- mlr3pipelines-0.3.3/mlr3pipelines/R/PipeOpTuneThreshold.R | 3 + mlr3pipelines-0.3.3/mlr3pipelines/R/bibentries.R | 5 -- mlr3pipelines-0.3.3/mlr3pipelines/build/partial.rdb |binary mlr3pipelines-0.3.3/mlr3pipelines/man/mlr_learners_avg.Rd | 2 - mlr3pipelines-0.3.3/mlr3pipelines/tests/testthat/test_pipeop_textvectorizer.R | 5 +- 10 files changed, 26 insertions(+), 27 deletions(-)
Title: Imagine Your Data Before You Collect It
Description: Helps you imagine your data before you collect it. Hierarchical data structures
and correlated data can be easily simulated, either from random number generators or
by resampling from existing data sources. This package is faster with 'data.table' and
'mvnfast' installed.
Author: Graeme Blair [aut, cre],
Jasper Cooper [aut],
Alexander Coppock [aut],
Macartan Humphreys [aut],
Aaron Rudkin [aut],
Neal Fultz [aut]
Maintainer: Graeme Blair <graeme.blair@ucla.edu>
Diff between fabricatr versions 0.12.0 dated 2021-01-09 and 0.14.0 dated 2021-02-09
DESCRIPTION | 8 - MD5 | 22 ++-- NAMESPACE | 1 NEWS.md | 4 R/add_level.R | 31 +++--- R/draw_multivariate.R | 3 R/modify_level.R | 19 ++- R/nest_level.R | 81 ++++++++++++---- R/potential_outcomes.R | 2 tests/testthat/test-helper-functions.R | 6 - tests/testthat/test-hierarchical.R | 24 ++++ tests/testthat/test-potential-outcomes.R | 152 +++++++++++++++++++++++++++++-- 12 files changed, 282 insertions(+), 71 deletions(-)
Title: Kernel Density Estimation using Lifetime Distributions
Description: A collection of asymmetrical kernels belong to lifetime distributions for kernel density estimation is presented.
Mean Squared Errors (MSE) are calculated for estimated curves. For this purpose, R functions allow the distribution to be Gamma, Exponential or Weibull.
For details see Chen (2000a, b), Jin and Kawczak (2003) and Salha et al. (2014) <doi:10.12988/pms.2014.4616>.
Author: Javaria Ahmad Khan, Atif Akbar.
Maintainer: Javaria Ahmad Khan <jakhan0@yahoo.com>
Diff between DELTD versions 2.6.6 dated 2020-11-19 and 2.6.7 dated 2021-02-09
DESCRIPTION | 6 ++-- MD5 | 24 ++++++++--------- R/DELTD.R | 69 +++++++++++++++++++-------------------------------- man/BS.Rd | 8 ++--- man/Beta.Rd | 8 ++--- man/DELTD-package.Rd | 25 +----------------- man/Erlang.Rd | 4 +- man/Gamma.Rd | 12 +++++--- man/LogN.Rd | 6 ++-- man/mse.Rd | 4 +- man/plot.Beta.Rd | 2 - man/plot.Gamma.Rd | 2 - man/plot.LogN.Rd | 2 - 13 files changed, 69 insertions(+), 103 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-09-24 0.1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-12-17 0.1.1
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-11-28 0.4.5
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2018-11-16 1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-04-17 1.0.0
2019-07-03 0.1.1
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-12-16 3.3
2018-04-03 3.2
2017-12-21 3.0
2017-05-11 2.0
2016-03-07 1.4
2016-03-06 1.3
2015-12-22 1.2
2015-06-08 1.1
2014-12-05 1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-12-01 1.6.9
2019-02-07 1.6.5
2018-08-06 1.6.4
Title: Variance-Adjusted Mahalanobis
Description: Contains logic for cell-specific gene set scoring of single cell RNA sequencing data.
Author: H. Robert Frost
Maintainer: H. Robert Frost <rob.frost@dartmouth.edu>
Diff between VAM versions 0.5.0 dated 2021-02-01 and 0.5.1 dated 2021-02-09
DESCRIPTION | 10 ++++--- MD5 | 28 ++++++++++++---------- NAMESPACE | 1 NEWS | 7 +++++ R/SeuratWrapperForVAM.R | 28 ++++++++++++++-------- build/vignette.rds |binary inst/doc/VAM_PBMC3K_Hallmark_LogNormalization.pdf |binary inst/doc/VAM_PBMC3K_LogNormalization.pdf |binary inst/doc/VAM_PBMC3K_SCTransform.pdf |binary inst/doc/VAM_pbmc_small.R | 15 ++++------- inst/doc/VAM_pbmc_small.Rnw | 5 --- inst/doc/VAM_pbmc_small.pdf |binary inst/doc/VAM_pbmc_small_sctransform.R |only inst/doc/VAM_pbmc_small_sctransform.Rnw |only inst/doc/VAM_pbmc_small_sctransform.pdf |only vignettes/VAM_pbmc_small.Rnw | 5 --- vignettes/VAM_pbmc_small_sctransform.Rnw |only 17 files changed, 57 insertions(+), 42 deletions(-)